1. Technical Field
One or more embodiments relate generally to editing optical character recognition errors. More specifically, one or more embodiments relate to editing optical character recognition errors using inline contextual image previews.
2. Background and Relevant Art
Optical character recognition (referred to herein as OCR) is a useful feature that allows a computing device to recognize text in an image and convert the text of the image into machine-readable text. For example, users can download, photograph, or scan books to obtain an image including text. The users can perform OCR on the image so as to recognize the text in the image, thereby allowing a user to select, copy, search, and edit the text.
Conventional OCR systems, however, frequently produce OCR errors when recognizing text. Common errors include unrecognizable or improperly converted text. OCR errors can often render converted text unusable until a user corrects the errors. Improperly converted text can occur, for instance, when an image may has a low resolution, blurred text, and/or unclear text. In another instance, conventional OCR systems may improperly convert text because the image may include uncommon characters or an underlying adjacent graphic that obscures the text. Furthermore, OCR systems can recognize illustrations in an image as text when the illustration does not actually include text.
In many instances, conventional OCR systems provide converted texts in an invisible layer superimposed on the image itself. As such, when a user selects text within the image, the user is selecting text in the hidden layer of converted text. If the text is improperly converted, however, the user may select text that is different from what appears to be selected. In other words, the user may believe he or she is selecting the text as shown in the image when the user is actually selecting the improperly converted text in the hidden layer. As such, a user may not discover OCR errors until trying to copy the improperly converted text into another document.
Alternative OCR systems, rather than providing an invisible layer with converted text, replace the text in the source image with system fonts. In this manner, the OCR system replaces the original text in the image with the recognized text using system fonts. Attempting to correct OCR errors in the recognized text, however, may be difficult, as the user cannot view the original image as the image has been replaced with system fonts. As such, the user is left to guess how to correct the text because the original source image is hidden or overwritten.
Some conventional systems provide a separate user interface to assist the user in correcting suspect text. Such separate user interfaces may provide a preview of the suspect word as shown in the source image. Under this approach, however, the user must switch back and forth between viewing the machine-readable document and the separate user interface. In transitioning back and forth, the user can easily lose track of where the suspect text is in the machine-readable document, thus, adding confusion to the correction process. Overall, the process of correcting OCR errors using separate user interfaces is often tedious and frustrating.
Thus, there are several disadvantages to current methods for correcting, editing, and reviewing OCR errors.